Automatic speech recognition (ASR) techniques may be employed in computer systems and other electronic systems to recognize human speech. The speech may be recognized as words, phrases, sentences, commands, or other such speech elements. The performance of ASR presents various challenges related to environmental distortion. Estimating distortion parameters accurately can be quite difficult. One cause of poor ASR performance is a mismatch between training conditions and operating conditions. For example, systems may be trained without environmental distortion or noise, while operating conditions may include varying environmental distortions and noise. In traditional ASR methods, acoustic models are frequently trained using clean speech without noise or distortion.
It is with respect to these considerations and others that the disclosure made herein is presented.